Systems and methods of simulating a physical bond layer comprising a composite material and predicting one or more properties of the composite material are disclosed. A method includes obtaining one or more X-ray images of a bulk physical sample of a composite material, the one or more X-ray images including one or more visual identifiers that correspond to one or more materials present in the bulk physical sample, and generating a three dimensional image of the bulk physical sample from the one or more X-ray images. The three dimensional image includes one or more labels indicating the presence and location of the one or more materials. The method further includes creating a meshed three dimensional microstructure-based model from the three dimensional image and simulating a physical bond layer with the meshed three dimensional microstructure-based model. The meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels.
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1. A method of simulating a digital representation of a physical bond layer, the method comprising: creating a bulk physical sample of a composite material usable between an electronic device and a substrate in an assembly; obtaining one or more X-ray images of the bulk physical sample, the one or more X-ray images comprising one or more visual identifiers that correspond to one or more materials present in the bulk physical sample; generating a three dimensional image of the bulk physical sample from the one or more X-ray images, wherein the three dimensional image comprises one or more labels indicating the presence and location of the one or more materials; creating a meshed three dimensional microstructure-based model from the three dimensional image, wherein the meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels; and simulating the digital representation of the physical bond layer using the meshed three dimensional microstructure-based model.
This invention relates to simulating the behavior of a physical bond layer in electronic device assemblies. The problem addressed is the need for accurate digital representations of composite materials used in bonding electronic devices to substrates, which is critical for predicting performance and reliability. The method involves creating a bulk physical sample of the composite material and capturing X-ray images to identify and locate different materials within the sample. These X-ray images are processed to generate a three-dimensional image with labels indicating material presence and location. The labeled 3D image is then converted into a meshed microstructure-based model that incorporates the material data. This model is used to simulate the digital representation of the bond layer, enabling detailed analysis of its properties and behavior. The approach leverages high-resolution imaging and modeling to create a precise digital twin of the physical bond layer, improving design and testing processes for electronic assemblies. The method ensures accurate material representation and spatial distribution, which are essential for reliable simulations.
2. The method of claim 1 , wherein creating the bulk physical sample comprises creating the bulk physical sample via solder, Ag sinter, or TLP bonding.
This invention relates to methods for creating bulk physical samples, particularly in the context of semiconductor packaging or microelectronic assembly. The problem addressed is the need for reliable and efficient bonding techniques to form bulk physical samples, which are often used for testing, prototyping, or manufacturing validation. Traditional bonding methods may suffer from issues such as poor thermal or electrical conductivity, mechanical instability, or inadequate bonding strength. The invention describes a method where a bulk physical sample is created using advanced bonding techniques, specifically solder, silver (Ag) sintering, or transient liquid phase (TLP) bonding. Solder bonding involves melting a solder material to join components, providing good electrical and thermal conductivity but may require higher temperatures. Ag sintering uses silver particles that are sintered at lower temperatures to form a strong, conductive bond, suitable for high-reliability applications. TLP bonding involves a temporary liquid phase that solidifies into a stable intermetallic compound, offering high thermal stability and mechanical strength. These bonding methods ensure robust connections in the bulk physical sample, improving performance and durability in electronic devices. The invention focuses on optimizing these bonding techniques to enhance the quality and reliability of the resulting bulk physical sample.
3. The method of claim 1 , wherein creating the bulk physical sample comprises: combining a first material having a high melting temperature with a second material having a low melting temperature to obtain a combination; and applying heat to the combination such that the combination has an average internal temperature that is greater than a melting point temperature of the first material and less than a melting point temperature of the second material, wherein applying the heat causes the first material to melt and diffuse between portions of the second material, forming intermetallic compounds between the first material and the second material.
This invention relates to a method for creating a bulk physical sample by combining materials with different melting temperatures to form intermetallic compounds. The process addresses challenges in material synthesis where achieving uniform distribution and bonding between dissimilar materials is difficult due to their differing thermal properties. The method involves combining a first material with a high melting temperature and a second material with a low melting temperature. Heat is applied to the combination such that the average internal temperature is maintained above the melting point of the first material but below the melting point of the second material. This controlled heating causes the first material to melt and diffuse between the solid portions of the second material, resulting in the formation of intermetallic compounds between the two materials. The technique ensures strong bonding and uniform distribution of the first material within the second material, overcoming limitations in traditional material synthesis methods. The resulting bulk sample exhibits enhanced mechanical, thermal, or electrical properties due to the intermetallic compound formation. This approach is particularly useful in applications requiring high-performance composite materials, such as aerospace, automotive, or electronics industries.
4. The method of claim 1 , further comprising predicting one or more properties of the composite material with the simulated digital representation of the physical bond layer.
This invention relates to digital simulation and analysis of composite materials, specifically focusing on predicting properties of a composite material by simulating a physical bond layer between material components. Composite materials often consist of multiple layers or components bonded together, and their performance depends heavily on the integrity and properties of these bond layers. The challenge is accurately predicting how these bond layers behave under various conditions to optimize material design and performance. The method involves creating a simulated digital representation of the physical bond layer within a composite material structure. This simulation accounts for the bond layer's material properties, geometry, and interaction with adjacent layers. By analyzing this digital representation, the method predicts one or more properties of the composite material, such as strength, durability, or thermal conductivity. The simulation may incorporate factors like stress distribution, adhesion quality, or environmental effects to refine predictions. This approach enables engineers to assess composite material performance before physical prototyping, reducing development time and costs. The method is particularly useful in industries like aerospace, automotive, and construction, where composite materials are widely used. By accurately modeling bond layers, the invention helps ensure that composite materials meet required performance standards while optimizing design efficiency.
5. The method of claim 4 , further comprising comparing the predicted one or more properties of the composite material with one or more properties of the bulk physical sample.
This invention relates to the field of material science and composite material analysis, specifically addressing the challenge of accurately predicting and validating the properties of composite materials. The method involves generating a digital twin of a composite material, which is a virtual representation that simulates the material's behavior under various conditions. This digital twin is created by processing input data, such as material composition, manufacturing parameters, and environmental factors, through a machine learning model. The model predicts one or more properties of the composite material, such as strength, durability, or thermal conductivity. The method further includes comparing the predicted properties of the composite material with the actual properties of a bulk physical sample of the same material. This comparison helps validate the accuracy of the digital twin and the machine learning model, ensuring that the predictions align with real-world performance. The comparison step may involve statistical analysis, error metrics, or other validation techniques to assess the model's reliability. By integrating this validation process, the method improves the trustworthiness of the digital twin for applications in material design, quality control, and performance optimization. The overall approach enhances the efficiency and accuracy of composite material development by reducing the need for extensive physical testing.
6. The method of claim 1 , wherein simulating the digital representation of the physical bond layer comprises applying a load to the meshed three dimensional microstructure-based model and performing a finite element analysis test to simulate physical testing of the physical bond layer.
This invention relates to simulating the behavior of physical bond layers in materials, particularly for evaluating structural integrity and performance under load conditions. The method involves creating a meshed three-dimensional microstructure-based model of the bond layer, which captures its internal geometric and material properties at a fine scale. A load is then applied to this model, and a finite element analysis (FEA) test is performed to simulate physical testing of the bond layer. The FEA test evaluates how the bond layer deforms, stresses, and potentially fails under the applied load, providing insights into its mechanical behavior. This approach allows for virtual testing of bond layers without physical prototyping, reducing costs and accelerating material development. The method is particularly useful in industries like aerospace, automotive, and construction, where bond layer performance is critical. By simulating real-world conditions, the technique helps identify potential weaknesses and optimize material designs before manufacturing. The microstructure-based modeling ensures accurate representation of the bond layer's internal structure, improving the reliability of the simulation results.
7. The method of claim 1 , wherein: generating the three dimensional image comprises generating, by a processing device, the three dimensional image; and creating the meshed three dimensional microstructure-based model comprises creating, by the processing device, the meshed three dimensional microstructure-based model.
This invention relates to the field of three-dimensional (3D) imaging and modeling, specifically for generating detailed microstructure-based models. The problem addressed is the need for accurate and computationally efficient methods to create high-resolution 3D models that capture fine structural details, such as those found in biological tissues, materials, or complex geometries. The method involves generating a 3D image of an object using a processing device, where the image captures the object's microstructure with high fidelity. This 3D image is then used to create a meshed 3D microstructure-based model, also generated by the processing device. The meshing process involves discretizing the 3D image into a structured or unstructured grid, allowing for detailed analysis or simulation of the object's properties. The processing device ensures that the model accurately represents the microstructure, enabling applications in fields such as medical imaging, materials science, and engineering simulations. The method improves upon existing techniques by leveraging computational processing to enhance both the resolution and efficiency of microstructure modeling.
8. The method of claim 1 , wherein the one or more visual identifiers are selected from a gray area, a shading, a pattern, a gradient, and a stippling.
The invention relates to a method for enhancing visual representations, particularly in digital displays or printed materials, to improve clarity and user interaction. The method addresses the challenge of effectively conveying information through visual identifiers that are easily distinguishable and intuitive for users. The core technique involves applying specific visual identifiers to elements within a display or document to highlight or differentiate them from other content. These identifiers are chosen from a set of options including gray areas, shading, patterns, gradients, and stippling. Each identifier type serves to modify the appearance of the underlying content in a way that draws attention or provides contextual meaning without obscuring the original information. For example, shading may be used to indicate a selected area, while patterns or gradients could denote different data categories or levels of importance. The method ensures that the identifiers are applied in a manner that maintains readability and aesthetic coherence while achieving the desired visual distinction. This approach is particularly useful in applications where visual clarity is critical, such as in data visualization, user interfaces, or technical documentation.
9. The method of claim 1 , wherein the one or more visual identifiers comprises a first visual identifier corresponding to a first material present in the bulk physical sample and a second visual identifier corresponding to a second material present in the bulk physical sample.
This invention relates to a method for analyzing bulk physical samples to identify and distinguish different materials within the sample using visual identifiers. The method addresses the challenge of accurately detecting and characterizing multiple materials in a mixed or composite sample, which is critical in fields such as quality control, environmental monitoring, and material science. The method involves capturing visual data of the bulk physical sample, which may include images, spectral data, or other visual representations. The captured data is processed to identify one or more visual identifiers that correspond to distinct materials present in the sample. Specifically, the method distinguishes between at least a first material and a second material within the sample by associating a first visual identifier with the first material and a second visual identifier with the second material. These identifiers may be based on unique visual characteristics, such as color, texture, or spectral signatures, that differentiate the materials. The method may further include analyzing the spatial distribution of the identified materials within the sample, quantifying their relative amounts, or mapping their locations. This enables detailed material characterization, which can be used for applications such as material sorting, contamination detection, or compositional analysis. The approach is particularly useful for samples where materials are intermixed or layered, providing a non-destructive way to assess their composition.
10. The method of claim 1 , further comprising optimizing the digital representation of the physical bond layer for a particular application by manipulating the meshed three dimensional microstructure-based model to obtain particular properties of the physical bond layer.
This invention relates to optimizing the digital representation of a physical bond layer for specific applications by manipulating a meshed three-dimensional microstructure-based model. The method involves creating a digital representation of the bond layer, which includes a microstructure-based model that defines the internal geometry and properties of the material. This model is then converted into a meshed three-dimensional structure, allowing for detailed analysis and modification. The optimization process adjusts the meshed model to achieve desired properties in the physical bond layer, such as strength, flexibility, or thermal conductivity, by altering the microstructure geometry or material distribution. The optimized digital model can then be used to fabricate the physical bond layer with the targeted properties. This approach enables precise control over material performance by leveraging computational modeling and simulation to tailor the microstructure for specific applications, such as adhesives, coatings, or composite materials. The method ensures that the final product meets performance requirements while minimizing material waste and improving efficiency in manufacturing processes.
11. The method of claim 1 , further comprising constructing the physical bond layer for use between the electronic device and the substrate in the assembly such that the physical bond layer binds the electronic device and the substrate and exhibits the particular properties.
This invention relates to the assembly of electronic devices onto substrates, addressing challenges in achieving reliable physical bonding while maintaining specific material properties. The method involves constructing a physical bond layer between an electronic device and a substrate to securely attach them while ensuring the bond layer exhibits desired properties, such as thermal conductivity, electrical insulation, or mechanical strength. The bond layer is engineered to meet these requirements, ensuring optimal performance in electronic assemblies. The process may include selecting materials, applying bonding agents, or adjusting layer thickness to achieve the necessary characteristics. This approach enhances the durability and functionality of electronic devices in various applications, such as semiconductor packaging or printed circuit board assembly, by ensuring the bond layer meets performance criteria without compromising device integrity. The method is particularly useful in environments where thermal management, electrical isolation, or mechanical stability is critical.
12. A system for optimizing a digital representation of a physical bond layer comprising a composite material from a bulk physical sample of the composite material that is usable between an electronic device and a substrate in an assembly, the system comprising: a processing device; and a non-transitory, processor readable storage medium, the non-transitory, processor readable storage medium comprising one or more programming instructions stored thereon that, when executed by the processing device, cause the processing device to: obtain one or more X-ray images of a bulk physical sample of the composite material, the one or more X-ray images comprising one or more visual identifiers that correspond to one or more materials present in the bulk physical sample; generate a three dimensional image of the bulk physical sample from the one or more X-ray images, wherein the three dimensional image comprises one or more labels indicating the presence and location of the one or more materials; create a meshed three dimensional microstructure-based model from the three dimensional image, wherein the meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels; simulate the digital representation of the physical bond layer using the meshed three dimensional microstructure-based model; and optimize the digital representation of the physical bond layer for a particular application by manipulating the meshed three dimensional microstructure-based model to obtain particular properties of the physical bond layer.
This system optimizes a digital representation of a physical bond layer made from a composite material used between an electronic device and a substrate. The system addresses challenges in accurately modeling and optimizing composite materials for specific applications by leveraging X-ray imaging and computational simulation. A processing device executes instructions stored on a non-transitory storage medium to perform several steps. First, it obtains X-ray images of a bulk physical sample of the composite material, where the images contain visual identifiers corresponding to different materials in the sample. These images are then used to generate a three-dimensional image of the sample, with labels indicating the presence and location of the materials. Next, a meshed three-dimensional microstructure-based model is created from this image, incorporating the labeled material data. The system simulates the digital representation of the bond layer using this model and optimizes it for a particular application by manipulating the model to achieve desired properties. This approach enables precise digital modeling and optimization of composite bond layers for improved performance in electronic assemblies.
13. The system of claim 12 , wherein the non-transitory, processor readable storage medium further comprises one or more programming instructions stored thereon that, when executed by the processing device, cause the processing device to: predict one or more properties of the composite material with the simulated digital representation of the physical bond layer.
This invention relates to a computational system for simulating and analyzing composite materials, particularly focusing on the properties of bond layers within such materials. The system addresses the challenge of accurately predicting the behavior of composite materials, which often involve complex interactions between different layers. Traditional methods of material testing are time-consuming and costly, making computational simulation a valuable alternative. The system includes a processing device and a non-transitory, processor-readable storage medium containing programming instructions. These instructions enable the processing device to generate a simulated digital representation of a physical bond layer within a composite material. The bond layer is a critical interface between different material components, and its properties significantly influence the overall performance of the composite. The system further includes instructions to predict one or more properties of the composite material based on this simulated bond layer representation. These properties may include mechanical strength, thermal conductivity, or other performance metrics relevant to the material's intended application. The simulation accounts for various factors such as material composition, layer thickness, and environmental conditions, allowing for accurate predictions without physical prototyping. This capability is particularly useful in industries like aerospace, automotive, and construction, where material performance is critical. By leveraging computational modeling, the system reduces development time and costs while improving the reliability of composite material design.
14. The system of claim 13 , wherein the non-transitory, processor readable storage medium further comprises one or more programming instructions stored thereon that, when executed by the processing device, cause the processing device to: compare the predicted one or more properties of the composite material with one or more properties of the bulk physical sample.
This invention relates to a system for analyzing composite materials, addressing the challenge of accurately predicting material properties before physical production. The system includes a processing device and a non-transitory, processor-readable storage medium storing programming instructions. These instructions, when executed, enable the system to predict one or more properties of a composite material based on input data, such as material composition, processing conditions, or structural parameters. The system then compares these predicted properties with the properties of an actual bulk physical sample of the composite material. This comparison allows for validation of the predictive model, ensuring accuracy in material design and manufacturing. The system may also include a user interface for inputting data and displaying results, as well as a database for storing material property data. The comparison step helps identify discrepancies between predicted and measured properties, enabling refinements in the predictive model or adjustments in material formulation. This approach reduces trial-and-error in material development, saving time and resources.
15. The system of claim 12 , wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to simulate the digital representation of the physical bond layer further cause the processing device to: apply a load to the meshed three dimensional microstructure-based model; and perform a finite element analysis test to simulate physical testing of the physical bond layer.
This invention relates to a computational system for simulating and analyzing the mechanical behavior of physical bond layers, such as adhesives or coatings, in engineering applications. The system addresses the challenge of accurately predicting the performance of these materials under real-world conditions, which is critical for designing reliable structures in industries like aerospace, automotive, and construction. The system includes a processing device that executes programming instructions to create a digital representation of a physical bond layer. This representation is based on a meshed three-dimensional microstructure-based model, which captures the detailed internal structure of the material. The system applies a load to this model and performs a finite element analysis (FEA) test to simulate physical testing of the bond layer. This allows engineers to evaluate stress distribution, deformation, and failure mechanisms without physical prototyping. The FEA test involves solving mathematical equations that describe the material's behavior under applied loads, providing insights into how the bond layer will perform in actual use. By simulating different loading conditions, the system helps optimize material properties and design configurations to enhance durability and performance. This approach reduces development time and costs while improving the reliability of bonded structures.
16. The system of claim 12 , wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to obtain one or more X-ray images further cause the processing device to electronically receive the one or more X-ray images via a user input.
Technical Summary: This invention relates to a medical imaging system designed to enhance the analysis of X-ray images. The system addresses the challenge of efficiently capturing and processing X-ray data for diagnostic purposes, particularly in environments where manual input or user interaction is required. The system includes a processing device configured to execute programming instructions that obtain one or more X-ray images. Specifically, the system is capable of electronically receiving X-ray images through a user input, allowing for direct data acquisition from a user interface or input device. This feature ensures flexibility in how X-ray images are integrated into the system, accommodating various input methods such as manual uploads, digital transfers, or direct capture from imaging devices. The system may also include additional components, such as a display for visualizing the X-ray images and a memory for storing the data. The overall design aims to streamline the workflow in medical imaging by enabling seamless integration of X-ray data into the analysis process, improving efficiency and accuracy in diagnostic evaluations.
17. The system of claim 12 , wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to obtain one or more X-ray images further cause the processing device to electronically receive the one or more X-ray images from an X-ray device.
This invention relates to a system for processing X-ray images, addressing the need for efficient and automated handling of radiographic data in medical or industrial applications. The system includes a processing device configured to execute programming instructions to obtain one or more X-ray images, where the images are electronically received from an X-ray device. The system further includes a memory storing the X-ray images and a display device for presenting the images to a user. The processing device is capable of analyzing the X-ray images to detect and highlight specific features, such as anomalies or regions of interest, and may apply image enhancement techniques to improve visibility. The system may also include a user interface allowing operators to adjust settings, annotate images, or control the X-ray device. The invention aims to streamline workflows by automating image acquisition, processing, and display, reducing manual intervention and improving diagnostic accuracy or inspection efficiency. The system may be integrated into medical imaging workflows, industrial non-destructive testing, or other applications requiring X-ray analysis.
18. The system of claim 12 , wherein the one or more programming instructions that, when executed by the processing device, cause the processing device to optimize the digital representation of the physical bond layer further cause the processing device to: apply one or more optimization algorithms to the digital representation of the physical bond layer to determine a composition of the bulk physical sample that has one or more of a particular Young's modulus and a particular coefficient of thermal expansion property for the particular application.
This invention relates to optimizing the design of physical bond layers in composite materials to achieve specific mechanical and thermal properties. The system digitally represents a physical bond layer between two or more materials and optimizes its composition to meet desired performance criteria. The optimization process involves applying algorithms to the digital representation to determine the ideal composition of the bulk physical sample. These algorithms analyze the bond layer's properties, such as Young's modulus and coefficient of thermal expansion, to ensure they match the requirements of a specific application. By adjusting the bond layer's composition, the system ensures that the final material exhibits the necessary mechanical strength, flexibility, and thermal stability. This approach is particularly useful in industries where precise control over material properties is critical, such as aerospace, automotive, and electronics manufacturing. The system automates the optimization process, reducing the need for trial-and-error testing and accelerating material development. The digital representation allows for rapid iteration and refinement of the bond layer design, ensuring that the final product meets performance specifications efficiently.
19. A method for predicting one or more properties of a composite material, the method comprising: creating a bulk physical sample of the composite material that is usable between an electronic device and a substrate in an assembly; arranging the bulk physical sample at an X-ray machine such that the X-ray machine generates one or more X-ray images of the bulk physical sample, the one or more X-ray images comprising one or more visual identifiers that correspond to one or more materials present in the bulk physical sample; generating a three dimensional image of the bulk physical sample from the one or more X-ray images, wherein the three dimensional image comprises one or more labels indicating the presence and location of the one or more materials; creating a meshed three dimensional microstructure-based model from the three dimensional image, wherein the meshed three dimensional microstructure-based model incorporates data obtained from the one or more labels; simulating a digital representation of a physical bond layer using the meshed three dimensional microstructure-based model; predicting the one or more properties of the composite material with the simulated digital representation of the physical bond layer; and optimizing the digital representation of the physical bond layer for a particular application by using the meshed three dimensional microstructure-based model to obtain particular properties of the physical bond layer.
This method relates to predicting properties of composite materials used in electronic device assemblies. The technique addresses challenges in accurately characterizing and optimizing composite materials, particularly those forming bond layers between electronic devices and substrates. The process begins by creating a bulk physical sample of the composite material. The sample is scanned using an X-ray machine to generate multiple X-ray images, which reveal visual identifiers corresponding to different materials within the sample. These images are combined to produce a three-dimensional representation of the sample, with labels indicating the presence and location of each material. A meshed three-dimensional microstructure-based model is then created from this labeled image, incorporating the material distribution data. This model is used to simulate a digital representation of the physical bond layer, enabling prediction of the composite material's properties. The digital representation is further optimized for specific applications by adjusting the model to achieve desired properties in the bond layer. The method leverages high-resolution imaging and computational modeling to enhance material characterization and performance prediction in electronic assemblies.
20. The method of claim 19 , wherein creating the bulk physical sample comprises: combining a first material having a high melting temperature with a second material having a low melting temperature to obtain a combination; and applying heat to the combination such that the combination has an average internal temperature that is greater than a melting point temperature of the first material and less than a melting point temperature of the second material, wherein applying the heat causes the first material to melt and diffuse between portions of the second material, forming intermetallic compounds between the first material and the second material.
This invention relates to a method for creating a bulk physical sample by combining materials with different melting temperatures to form intermetallic compounds. The problem addressed is the need for efficient material processing techniques that produce strong, uniform composites with enhanced properties through controlled melting and diffusion. The method involves combining a first material with a high melting temperature and a second material with a low melting temperature. The combined materials are then heated to an average internal temperature that exceeds the melting point of the first material but remains below the melting point of the second material. This controlled heating causes the first material to melt and diffuse between the portions of the second material, resulting in the formation of intermetallic compounds between the two materials. The process ensures that the second material remains solid while the first material melts, facilitating uniform distribution and bonding. This technique is particularly useful in manufacturing advanced composites where the properties of both materials are leveraged to create a stronger, more durable final product. The method avoids excessive heating that could degrade the second material while ensuring proper diffusion and bonding of the first material. The resulting bulk sample exhibits improved mechanical and thermal properties due to the intermetallic compounds formed during the process.
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February 17, 2016
November 26, 2019
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